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labmlai annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Stars
67,390
Forks
6,754
Watchers: 67,390
Language
License: MIT License
Repository Radar Score
47 / 100
Growth
- 7d
- +0
- 30d
- +0
- %
- 0.0%
Not enough metric snapshots yet to chart growth for this repository.
Score breakdown
- popularity 89
- growth 0
- activity 15
- freshness 100
- community 70
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Get a quote →This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,
The website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better.
We are actively maintaining this repo and adding new
implementations almost weekly.
for updates.
- JAX implementation
- Multi-headed attention
- Triton Flash Attention
- Transformer building blocks
- Transformer XL
- Rotary Positional Embeddings
- Attention with Linear Biases (ALiBi)
- RETRO
- Compressive Transformer
- GPT Architecture
- GLU Variants
- kNN-LM: Generalization through Memorization
- Feedback Transformer
- Switch Transformer
- Fast Weights Transformer
- FNet
- Attention Free Transformer
- Masked Language Model
- MLP-Mixer: An all-MLP Architecture for Vision
- Pay Attention to MLPs (gMLP)
- Vision Transformer (ViT)
- Primer EZ
- Hourglass
- Denoising Diffusion Probabilistic Models (DDPM)
- Denoising Diffusion Implicit Models (DDIM)
- Latent Diffusion Models
- Stable Diffusion
- Original GAN
- GAN with deep convolutional network
- Cycle GAN
- Wasserstein GAN
- Wasserstein GAN with Gradient Penalty
- StyleGAN 2
✨ LSTM
✨ ResNet
✨ U-Net
Solving games with incomplete information such as poker with CFR.
- Proximal Policy Optimization with Generalized Advantage Estimation
- Deep Q Networks with with Dueling Network, Prioritized Replay and Double Q Network.
- Adam
- AMSGrad
- Adam Optimizer with warmup
- Noam Optimizer
- Rectified Adam Optimizer
- AdaBelief Optimizer
- Sophia-G Optimizer
- Batch Normalization
- Layer Normalization
- Instance Normalization
- Group Normalization
- Weight Standardization
- Batch-Channel Normalization
- DeepNorm
pip install labml-nn
Repository Radar analysis
Deterministic insights derived from public metadata and our observations — not personal testing or reviews.
Why this repository is interesting
- High absolute popularity (67,390 stars) signals broad adoption.
Who should use it
- Developers working primarily with Python
- Teams exploring AI tooling, agents, or ML infrastructure
Potential use cases
- Reference or evaluate Python open-source approaches in this domain
- Prototype AI/agent workflows or study reference architectures
Strengths
- README present in our index
- Declared license: MIT License
- Substantial fork count (6,754) suggests reuse and contribution interest
Limitations / considerations
- Insights are derived from public metadata and our observations — not a substitute for code review
What to watch
- Re-check last push, issues, and releases on GitHub before production adoption
Strong signals: Strong community interest
Source: GitHub (public metadata) + Repository Radar analysis. We do not claim ownership of third-party repositories.